Barack Obama's campaign in 2012 was arguably the first to adopt big data as a differentiator in the elections. Obama's data advantage was such that the depth and breadth of the campaign's digital operation, from political and demographic data mining to voter sentiment and behavioural analysis, reached beyond anything politics had ever seen.
The Obama campaign management team launched a full-scale integrated campaign, leveraging TV, web, mobile, tele-calling, social media and analytics to directly target potential voters and donors with tailored messages during the lead up to the elections. They hired a multi-disciplinary team of statisticians, predictive modellers, data-mining experts, mathematicians, software programmers and quantitative analysts. One of the key tasks of this team was data consolidation. They worked on bringing together data from many disparate databases to create a single, massive system that merged information collected from pollsters, fundraisers, field workers and consumer databases as well as social-media and mobile contacts with the Democratic voter files. The advantage of having an integrated system is that analytics could be performed effectively across multiple datasets from multiple channels. Furthermore, the information could be shared across the entire organisation seamlessly, without multiple versions of the same data or potential data quality issues. A single version of truth is extremely critical for decision-making in such scenarios. The effective use of big data analytics in the Barack Obama campaign is cited by analysts as one of the major reasons for his victory.
As the ecosystem matures, expect more customised ads targeting specific groups rather than single ads being targeted at an entire demographic in the run-up to the general elections.
What the Obama campaign did in 2012, Prime Minister Modi did in 2014, though on a smaller scale. With the help of Prashant Kishor, Prime Minister Modi brought a professional touch to his campaign, making heavy use of data analytics and social media to craft messages that appealed to the people. Data analytics helped in refurbishing the engagement campaigns, as well as in creating appropriate strategies to increase voter engagement in key states. Data analytics also helped in recruiting volunteers and raising funds for the election.
Realising how big data and its resultant analysis can profoundly affect election campaigns and may even go on to determine winners, parties not just limited to the BJP or the Congress but even others such as AAP etc have begun to make use of our digital footprints to design electoral strategies. That said, however, it will be some time before personality profiling—right down to attitudinal factors revealed in consumer and lifestyle habits—can enable targeted ads directed at voters. Even in the build-up to the UP and Punjab elections, for example, touted as critical for the BJP and the Congress both, the ads being run continue to be largely focused on macro issues such as law and order and education. However, a more important aspect in these elections was to get first-time voters to come out to vote and that has been very successful thanks to the aggressive digital engagement strategies by campaign managers across the political parties. Irrespective of who wins or loses, the data from these elections will become important fodder for the next big elections—the 2019 general elections, now just a little over two years away. As the ecosystem matures, expect more customised ads targeting specific groups rather than single ads being targeted at an entire demographic in the run-up to the general elections.
The era of relying on gut instinct is over—a clear demonstration of analytics fuelled by big data and advancement in computing technology is now an integral part of the campaigning process.
On their part, politicians are increasingly taking the digital route to garner online influence. Prime Minister Modi, for example, has 27.1 million followers on Twitter (up from 8.5 million in 2014) and more than 39 million subscribe to his Facebook page. Younger politicians such as Rahul Gandhi or Akhilesh Yadav have 1.5 million and 2.4 million followers respectively. Being a youth leader and no stranger to the power of digital, Akhilesh even tweeted a photograph of him and his wife posing with the directors of Facebook recently. With billions of daily social media interactions, created with each Facebook like and share and a twitter tweet, Indians young and old alike, armed with a plethora of mobile devices, are leaving a huge digital footprint in their wake. Political brand managers are working relentlessly to find new ways to sort through this voluminous data to create, specific and targeted messaging for constituents and voters alike, which are no longer limited to election time. Instead, the idea is to provide them with a seamless user experience at all times, as they move between channels and touch points, whether TV, computer, mobile devices or tablets.
Are there any lessons to draw from the success of big data mining in elections? To begin with, the era of relying on gut instinct (usually predictions made by political experts) is over—a clear demonstration of analytics fuelled by big data and advancement in computing technology has now become an integral part of the campaigning process. But it's not just politics where this is relevant. Whether it's business and finance, the social sectors, government or scientific initiatives, a data-driven approach is more likely to create meaningful impact than a non-data-driven one. And for inspiration, the incredible case studies of how Obama, Modi and Trump won the digital battle will remain fresh for some time to come!